A description of how Media X serves as Stanford’s catalyst for innovation at the intersection of people and technology – across departments, and between university and business. Using socially constructed data, parsed from data retrieved from online English-language press releases, network analysis shows patterns of organizational infrastructure. The cultivation approach to global investments into Chinese technology-based companies is contrasted with the harvesting approach of Chinese investments into the rest of the world. Critical implications for board interlocks and flows of information are discussed. Research conducted at Media X at Stanford University, by Martha G. Russell, Neil Rubens, Kaisa Still, Jukka Huhtamaki

1. Insights Into InnovationMartha G RussellAssociate Director, Media X at Stanford UniversitySenior Research Scholar, HSTAR Institute August, 2010 Tokyo Contact: martha.russell@stanford.edu

2. H-STARHUMAN SCIENCES AND TECHNOLOGIES ADVANCED RESEARCH INSTITUTE Media X is Stanford's catalyst for industry and academic research into the impact of information and technology on society. Drawing on the world class capabilities of 93 Stanford researcher leaders in departments, centers and labs across the campus, Media X stimulates fundamental insights into innovation, helping accelerate successful outcomes. Media X research reduces risks for its member companies by providing cutting-edge knowledge on people and technology. Perspectives from the Stanford thought leaders provide ground-breaking insights and identify novel opportunities.

3. H-STARHUMAN SCIENCES AND TECHNOLOGIES ADVANCED RESEARCH INSTITUTE Media X Facts Media X catalyzes X-dept X-discipline research on IT and people questions, affiliated with HSTAR Institute 5 Professional Schools, all ranked in Top Ten Few other Universities have all 5, no other has 5 in Top Ten Draws on world class researchers across Stanford: Earth Sciences, Education, Engineering, Graduate School of Business, Humanities and Sciences, Law, Medicine Stanford sponsored research = ~$1B, ~$130M from industry 92 researchers and 150+ graduate students Founded in 2002, led by Silicon Valley’s Chuck House. Media X research is directed to issues that emerge from collaborative deliberations between our industry partners, H-STAR faculty and Media X leadership. Industry partners help select the actual projects and are invited to participate in the research.

4. MediaX Research Activities Span Stanford Labs Stanford University Medical Media & Information Technology SUMMIT Distributed Vision Lab DVL Electrical Engineering Psychology Psy Computer Science Virtual Human Interaction Lab, Communications between Humans and Interactive Media Lab EE Linguistics Ling Philosophy CS Com Phil SHL Stanford Humanities Lab Graduate School Of Business GSB VWG Virtual Worlds Group SCIL Stanford Center for Innovations in Learning CSLI Center for the Study Of Language & Information Art Digital Art Center Eng Engineering & Product Design Ed School of Education; Education and Learning Sciences PBLL Law Work Technology & Organization Des SSP Stanfor Joint Program in Design PBLL Law School LIFE Project Based Learning Laboratory Symbolic Systems Program Learning in Informal and Formal Environments

5. MEDIA X RESEARCH THEMES HAVE INCLUDED COLLABORATION Advanced human communication technologies.Exploring the fusion of virtual and physical worlds for advanced human communications. Interactive technologies for social interaction and collaboration. Using interactive technology in social interaction and collaboration in productivity contexts, including synchronous and asynchronous uses of text, graphics, voice and video. Use of mobile devices in collaboration. Researching mobile device-centric interactive technology used in collaboration in the context of multimedia. PARTICIPATION Online media content. Evaluating consumers as publishers or establish ontologies of content. Learning and training.Interactive technologies relating to learning and training, focusing on the integration of technology and an understanding of human psychology and social behavior to enhance understanding and performance. TECHNOLOGIES THAT ENABLE HUMAN-MACHINE INTERACTION Human-machine interaction and sensing.Research on human-machine interaction and sensing that focuses on the detection or sensing of human-comprehension, emotional states, gestures or touch. Ambient Intelligent Environments with sensing and control. The integration of technology and the understanding of human psychology and social behavior that can lead to new technologies that enable natural interaction with information and the physical world. Emotion detection from video capture of facial expression. Enabling vehicles to automatically perceive driver emotions and determine the driver's alertness/fatigue in order to provide a reliable and actionable safety index. IMAGE, SPEECH AND LANGUAGE PROCESSESING Natural language research:Basic and strategic research, training and technology transfer in speech and language processing. Video processing, cataloging, retrieval, and reuse.Using interactive technologies related to video processing, cataloging, retrieval and reuse, with a view to the development of automated systems to support video libraries. FORM FACTORS Mobile devices and alternative form factors.Researching mobile communication devices and services focusing on the device itself, the use cases for that device, the interface employed to render that device useful, and the connectivity opportunities and needs required to make that device part of the "connected" computing ecosystem.

6. Participation, Personalization and Emotion for Persuasion, Risk, and Reward Facial Expressions as Predictors of Online Buying Intention

7. Multitasking - Automated Participation Human- Machine Interaction Emotional determinants Personal vs. Product basis for HCI Multitasking Mental costs to media multitasking Performance costs to media multitasking Short-term orientation to memory of multitasked details

8. Rampant MultitaskingBroken, Outdated Monetization Models Atomization of markets (Chris Anderson) Simultaneous media exposure (Shultz, Pilotta) Multitasking is epidemic (Nass, Wagner) Emphasis on short-term memory Performance compromised Reach & Frequency are not sufficient CPM (the old business model) was based on this Most, If Not All, Current Media Advertising Models Are “Broken” or Irrelevant in the 21st Century Marketplace Are YOU talking to ME?

10. Engagement

11. Arousal

12. Trust

13. Referral

14. Neuroscience/Rodopsin

15. Associated Learning

17. Interest

18. Trial

19. Validation

20. Repeat

21. Loyalty

22. Measured by

23. Observation

24. Attitude

25. Behavior

26. Intention

28. Connected Business World increasingly influenced by Consumer World employees Consumer Enterprise partners Gaming Social media Social networking Cloud computing Text messaging Mobility MRP ERP HRM SCM KM Collaboration Petabytes of data suppliers customers

29. Communication Technologies Power InnovationPeople, Processes, Products Cope with consumerization Engage employees and customers Perceiving and analyzing change where it is already occurring Deploy capabilities and technology, within constrained budget Capture the business value Intel - Public August 3, 2008

30. Total Engagement

31. Leverage for Insight The Impact of Social Belief on the Neurophysiology of Memory Uses acquired equivalence paradigm to measure the extent to which learners are able to use the concept of memory-dependent logical inference as a basis for generalization Studies whether virtual contexts are optimal for learning and the expression of flexibly addressable knowledge Increase in hippocampal activity over the course of learning correlates with subsequent generalization of associations to a novel context.

32. Serious Games . . . • have a challenging goal• are fun and engaging • incorporate some form of scoring • impart to the user a skill, knowledge or attitude that can be applied in the real world

33. Multimodal Learning Experience Mediated by the Future Interactive Paper TextBook Multimodal Learning Experience Mediated by the Future Interactive Paper TextBook Study the continuum between learners’ dialogue and paper and pencil sketching To develop a model of the future interactive paper textbook Which will create and capture sharable and reusable items in context For example, to capture questions and thoughts of the textbook’s users and to communicate between the learner and the instructor, expert or author. A question forgotten or un-answered is a missed opportunity for learning

34. LIFE Research Network LIFE Executive Management Team Patricia K. Kuhl U of Washington John Bransford U of Washington Roy Pea Stanford University Dan Schwartz Stanford University Nora Sabelli SRI Intlernational Andrew Meltzhoff U of Washington LIFE Researchers at These Institutions University of California, San DiegoUniversity of Chicago University of Ottowa University of Texas, Austin University of Texas at San Antonio University of Vermont Georgia State University Kwantlen University College Portland State University Purdue University SRI International Stanford University

35. Informal Learning Arrangements . . . is recurring pattern of social, material and technological elements with which particular people teach and learn together. The discovery of naturally-occurring, diverse, and mostly efficacious learning arrangements invites new research questions about their density and distribution across social settings and demographics about the social, material, and technological conditions that make them efficacious about their relative efficaciousness when compared to designed learning arrangements

36. Semantic Integration Personal Area Networks: New Rules, New Metrics Semantic and functional integration across TV Computer Phone Home Car From clouds to the edge Ambient and intelligent Personalized Privacy-controlled Fluid media With many IP issues and measurement challenges

37. Metrics for Spread Salathe´ M, Jones JH (2010) Dynamics and Control of Diseases in Networks with Community Structure. PLoSComputBiol 6(4): e1000736. doi:10.1371/ journal.pcbi.1000736 James H Fowler and Nicholas A Christakis, “Dynamic Spread of Happiness in a Large Social Network:longitudinal analysis over 20 years in the Framingham Heart Study network,” BMJ 2008;337

38. Engagement Pinball CBS - Interview 6 million CBS - Debate 70 million Best rating in 14 years Web - Clips 3 million Second CBS - SNL Skit 14 million 17 million- 1st part First CBS - SNL Skit 9.5 million US Broadband penetration 2004 = 51% 2008 = ~90% Web - YouTube 25+ million More text messages than phone calls - first half of ‘08 Network Evening News audience 2008 = 21.9 million 2004 = 26 million The Vote: A Victory for Social Media, Too. The '08 election was a triumph for the likes of Facebook, Twitter, YouTube, and Flickr as voters chronicled their experiences in words, photos, video

39. Behavior Change in Energy ARPAe Grant One our of 3000 proposals 13 related interdisciplinary projects Infrastructure, interventions, Impact Computer infrastructure for prototyping and evaluation (software), Interventions, Smart Automation, Multiplayer game, Mobile Interactions, Policy and Incentives, Goals and Collective Action, School and community Programs, Energy Consumption Forecasts, Behaviorally informed prescriptive economic models, Open extensible communication network, “The U.S. has spent billions of dollars creating a smart infrastructure. Utilities are installing smart meters in homes to measure how much electricity is being consumed. But to be valuable, people need to be engaged with the information and use it to make good energy decisions.” Reeves “By combining technology systems and human behavior, will empower people to take charge of their electricity consumption decisions.” Sweeney

40. SPEED Limits Three years in the making, Speed Limits is a collaborative exhibition between the Canadian Center for Architecture and the Wolfsonian–FIU. The exhibition runs from May 20th to October 12th, 2009, at the Canadian Center for Architecture in Montreal, Canada.

41. Concert in Sirikata http://www.c6.tv/archivio?task=view&id=5820

42. Sensor Network Sensornets To develop virtual sensornets, which will allow scientists to construct instruments for measuring what is happening in virtual worlds, allow users to control and monitor what is being recorded, and provide an elegant and simple privacy mechanism.

43. Mehru - Sirikata

45. Silicon Valley The region’s economic power is a product of its past as well as its present, of military contracts as well as venture capital. Silicon Valley is an economically mature region whose childhood and adolescence were paid for by U.S. tax dollars – adaptation occurred on this foundation. “People change jobs here without even changing car pools.” “You could quit your job on Friday and have another one on Monday. You didn’t even have to tell you wife. You just drove off in another direction on Monday. You didn’t have to sell your house. Your kids didn’t even have to change schools.” http://images.google.com/imgres?imgurl=http://www.yorku.ca/anderson/Images/silicon_valley_3.jpg&imgrefurl=http://techiteasy.org/2007/02/13/&h=527&w=789&sz=108&hl=en&start=10&sig2=UfKH0Wg_EQFky-uYElh5Ug&um=1&usg=__j8qR006bzWFHYZznsPAAsLyIWlM=&tbnid=69kwEoq1mPXIiM:&tbnh=96&tbnw=143&ei=CEnaSOHnIJCksQOR1fnTAw&prev=/images%3Fq%3Dsilicon%2Bvalley%2Bpicture%26um%3D1%26hl%3Den%26sa%3DX

46. The new maps may be based on the connections - rather than on distance.

47. Distance Old New

48. Need for Updating Regional technology-based economic development “The global map of businesses is increasingly dominated by geographically concentrated groups of companies and related economic actors and institutions” The Use of Data and Analysis as a tool for cluster policy, Green Paper on international best practices and perspectives prepared for the European Commission, November 2008 “Members of a cluster can be sometimes located worldwide, but linked through information and communication technologies… the term e-cluster is used” Danese, Filippini, Romano, Vinelli 2009 “Technological trends are causing a change in the way innovation gets done in advanced market economies”Baldwin & von Hippel November 2009, Harvard Business School Working Paper 10-038 “Recognizing that a capacity to innovate and commercialize new high-technology products is increasingly a part of the international competition for economic leadership, governments around the world are taking active steps to strengthen their national innovation systems”Understanding Research, Science and Technology Parks: Global Best Practices, National Research Council of the National Academies, Report 2009

49. The Way We USED to Think About Organizations

50. The New Organizational Chart

51. Relationship Interlocks Executives and key employees Transfer of technologies and knowledge, professional networks, business culture, value-chain resources Directors US Fortune 500 firms interlocked (shared directors) with average 7 other firms Corporate governance embedded and filtered through social structures Executive compensation, strategies for takeovers, defending against takeovers Gerald F. Davis, “The Significance of Board Interlocks for Corporate Governance,” Corporate Governance 4:3, 1996 Investors and service providers Awareness of external forces, competitive insights, resource leverage Relationship interlocks provide Social relationship “filter” for governance, information flow & norms Transfer of implicit and explicit know-how Mental models http://fusionenterprises.ca/Business_Training.php

52. Innovation takes at least two.Team skills are required.There are winners and loosers. Although people can communicate anywhere, anytime, it’s difficult for anyone to have all the insights necessary at any one time for major decisions on the complex global issues Innovation is Social

53. The Knowledge Revolution is here. What can we learn to improve our play?

54. . Innovation Ecosystems Dataset 35,000 companies include: Sectors: Advertising, biotech, cleantech, consulting, ecommerce, enterprise, games_video, hardware, legal, mobile, network_hosting, public relations, search, security, semiconductor, software, web, other firms serving these. Investment profiles from Ltd to public, financing rounds identified Merger & Acquisition profiles Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” Technical Report. Media X, Stanford University, Feb.2010.

55. . Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” Technical Report. Media X, Stanford University, Feb.2010.

56. Networks of Female and Male Executives in Companies in the Clean Tech & Web Sectors Web Sector Clean Tech Sector Kaisa Still, Neil Rubens, Jukka Huhtamäki, and Martha Russell , “Networks of Executive s in Technology-Based Innovation Ecosystems,” Technical Report

57. Roles CTOs Investors CMOs Founders Kaisa Still, Neil Rubens, JukkaHuhtamäki, and Martha G. Russell , “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.

58. The Power of PullJohn Hagel, John Seely Brown, Lang Davison Sources of economic value creation have shifted to flows of knowledge and insights Pull creates platforms that enable responses to situations when they arise The network effect, the learning rate Just-in-time information Trust-based relationships

60. How are these patterns similar or different to those made by the rest of the world into China?http://successbeginstoday.org/wordpress/wp-content/unexpected2.jpg

62. 42 Chinese, 77 foreign investment firm

63. Investment into China US$ 5.4 B

64. Investment originating from China US$ 3.1 BInsights explored: The flow of financial resources into and out of China More illustrative than descriptive/prescriptive NodeXL, Tableau Innovation Ecosystem Network

65. More Specific: Context of eCIS sectoreCommerce and electronic security=eCommerce, software search, network hosting, mobile, games &video, enterprise Initial Data Analysis: 53% (113) of the Chinese companies from eCIS business sector 50 % (66) of the foreign companies are from the eCIS business sector Toward Insights about: Patterns and differences in the characteristics of investment flows into and from China Innovation Ecosystem Network

66. HARVESTInvestments from Chinese (making investments) Innovation Ecosystem Network

67. CULTIVATIONInvestments into China (receiving investments) Innovation Ecosystem Network

68. Network metrics Innovation Ecosystem Network

69. Emerging Chinese business clusters linked by investment firms Innovation Ecosystem Network

70. Topline Findings Cultivation / Harvesting modes - value co-creation Chinese interlocks at the investment firm level Government-led investment firms Knowledge of government guarantees Investments in firms that return benefits to China Global interlocks at both investment firm and enterprise levels Opportunity network & value co-creation http://successbeginstoday.org/wordpress/wp-content/unexpected2.jpg

71. Need for Updating Regional technology-based economic development “The global map of businesses is increasingly dominated by geographically concentrated groups of companies and related economic actors and institutions” The Use of Data and Analysis as a tool for cluster policy, Green Paper on international best practices and perspectives prepared for the European Commission, November 2008 “Members of a cluster can be sometimes located worldwide, but linked through information and communication technologies… the term e-cluster is used” Danese, Filippini, Romano, Vinelli 2009 “Technological trends are causing a change in the way innovation gets done in advanced market economies”Baldwin & von Hippel November 2009, Harvard Business School Working Paper 10-038 “Recognizing that a capacity to innovate and commercialize new high-technology products is increasingly a part of the international competition for economic leadership, governments around the world are taking active steps to strengthen their national innovation systems”Understanding Research, Science and Technology Parks: Global Best Practices, National Research Council of the National Academies, Report 2009

72. The Place for Innovation From localized to regional to virtual shared spaces Innovation Acceleration Networks !

73. Models of Innovation From organizations to single users to networked individuals eClusters !

74. Innovation Ecosystems Network Regional Studies with Global Perspective China, Norway, Finland

76. Sr. Research Scholar, HSTAR Institute

77. Associate Director, Media X at Stanford University

78. Neil Rubens, PhD, neil@hrstc.org

79. Assistant Professor, Graduate School of Information Systems

80. University of Electro-Communications, Tokyo

81. Jukka Huhtamäki, jukka.huhtamaki@tut.fi

82. Researcher, Lecturer

83. Hypermedia Laboratory (HLab) of Tampere University of Technology (TUT).

84. Kaisa Still, PhD, kaisastill@yahoo.com

85. Knowledge Management Specialist

86. Beijing DT Electronic Technology Co., Ltd

87. Mario Gastel, mariogastel@zeelandnet.nl

88. Graduate student, Texas Advertising, UT Austin

89. Fulbright Scholar (2009-11)

90. Jiafeng (Camilla) Yu, camillayu@gmail.com

91. M.A. in Advertising in Planning Track